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Research Engineer - Voice Intelligence

🇺🇸 United States

Machine Learning

Design

$200K - $300K

Research Engineer - Voice Intelligence

from 🇺🇸 United States

$200K - $300K

About Pocket

Take Notes in the Real World


Tech description:


Job description:

Pocket is building a category-defining platform for ambient intelligence. Voice is the highest-signal interface we have — and we’re looking for a research-minded engineer to push what’s possible with voice end-to-end: capture → understanding → real-time experiences → evaluation.

### **What you'll own**

* Invent and ship improvements to our voice stack: diarization, VAD, noise robustness, transcription quality, speaker ID, and post-processing.
* Build new voice-powered product capabilities: better memory, better meeting/voice summaries, better action extraction, better personalization.
* Run tight research loops: define metrics, build eval sets, iterate on models/algorithms, and productionize what works.
* Improve real-time performance and reliability: streaming pipelines, latency budgets, fallbacks, and graceful degradation.
* Partner closely with product + design to translate voice capabilities into features people feel immediately.

**What success looks like**

* Step-function improvements in voice quality and perceived intelligence (measured and felt).
* A clear evaluation harness (offline + online) that prevents regressions and accelerates iteration.
* Voice features that ship reliably at scale with predictable latency.

### **What we're looking for**

* Have 6–10+ years of experience shipping production systems with strong technical ownership.
* Are strong in applied ML/research engineering _and_ can turn prototypes into robust product.
* Understand audio/voice fundamentals (signal processing basics helpful) and modern model/eval workflows.
* Care deeply about performance and reliability.

**Nice-to-haves**

* Experience with streaming audio pipelines and real-time systems.
* Experience with LLM post-processing, structured extraction, and evaluation.
* Experience building tooling for labeling, dataset curation, and QA.

### **What we offer**

* Work directly with us and learn fast
* Direct impact on how the company operates day to day
* High-trust, high-responsibility environment
* Competitive compensation



by @maxrusakovic